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Exploration of compatibility rules and discovery of active ingredients in TCM formulas by network pharmacology

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Exploration of compatibility rules and discovery of active ingredients in TCM formulas by network pharmacology
Network pharmacology is an interdisciplinary field that utilizes computer science,technology,and bio-logical networks to investigate the intricate interplay among compounds/ingredients,targets,and dis-eases.Within the realm of traditional Chinese medicine(TCM),network pharmacology serves as a scientific approach to elucidate the compatibility relationships and underlying mechanisms of action in TCM formulas.It facilitates the identification of potential active ingredients within these formulas,pro-viding a comprehensive understanding of their holistic and systematic nature,which aligns with the holistic principles inherent in TCM theory.TCM formulas exhibit complexity due to their multi-component characteristic,involving diverse targets and pathways.Consequently,investigating their material basis and mechanisms becomes challenging.Network pharmacology has emerged as a valuable approach in TCM formula research,leveraging its holistic and systematic advantages.The manuscript aims to provide an overview of the application of network pharmacology in studying TCM formula com-patibility rules and explore future research directions.Specifically,we focus on how network pharmacol-ogy aids in interpreting TCM pharmacological theories and understanding formula compositions.Additionally,we elucidate the process of utilizing network pharmacology to identify active ingredients within TCM formulas.These findings not only offer novel research models and perspectives for integrat-ing network pharmacology with TCM theory but also present new methodologies for investigating TCM formula compatibility.All in all,network pharmacology has become an indispensable and crucial tool in advancing TCM formula research.

active ingredientscompatibility rulesmolecular mechanismnetwork analysisnetwork pharmacologysystems biologytarget predictiontraditional chinese medicine

Yishu Liu、Xue Li、Chao Chen、Nan Ding、Shiyu Ma、Ming Yang

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Longhua Hospital Affiliated to Shanghai University of Traditional Chinese Medicine,Shanghai 200032,China

Ruijin Hospital Affiliated to Shanghai Jiaotong University,Shanghai 200025,China

active ingredients compatibility rules molecular mechanism network analysis network pharmacology systems biology target prediction traditional chinese medicine

2024

10.1016/j.chmed.2023.09.008

中草药(英文版)
天津药物研究院 中国医学科学院药用植物研究所

中草药(英文版)

CSTPCD
影响因子：0.6
ISSN：1674-6384
年,卷(期)：2024.16(4)